class_docstr: A multi-head masked self-attention layer with a projection at the end.
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      _, seq_size, _ = x.size()
      y = self.attn(
          x, x, x, attn_mask=self.mask[0, 0, :seq_size, :seq_size]
      )[0]
      y = self.resid_drop(self.c_proj(y))
      return y
  
imports: import math
  from dataclasses import dataclass
  from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch.nn import functional
label_desc: Use image node_id 2 for calling the MultiheadAttentionLayer obj's underlying member method code with example usage: obj.forward(x) and returns: y